U.S. patent application number 15/016936 was filed with the patent office on 2017-08-10 for system and method for camera calibration by use of rotatable three-dimensional calibration object.
The applicant listed for this patent is SONY CORPORATION. Invention is credited to ALEXANDER BERESTOV, CHENG-YI LIU.
Application Number | 20170228864 15/016936 |
Document ID | / |
Family ID | 59496423 |
Filed Date | 2017-08-10 |
United States Patent
Application |
20170228864 |
Kind Code |
A1 |
LIU; CHENG-YI ; et
al. |
August 10, 2017 |
SYSTEM AND METHOD FOR CAMERA CALIBRATION BY USE OF ROTATABLE
THREE-DIMENSIONAL CALIBRATION OBJECT
Abstract
Various aspects of a system and a method for camera calibration
by use of a rotatable three-dimensional (3-D) calibration object
are disclosed herein. In accordance with an embodiment, the system
includes a first electronic device, which determines a rotation
pattern of the 3-D calibration object, based on a set of
pre-selected images. The set of pre-selected images includes the
3-D calibration object captured at pre-defined viewing angles.
Control information is communicated by the first electronic device
to a second electronic device associated with the 3-D calibration
object to rotate the 3-D calibration object in accordance with the
determined rotation pattern. A plurality of image frames of the 3-D
calibration object are captured to calibrate intrinsic and/or
extrinsic camera parameters of the first electronic device.
Inventors: |
LIU; CHENG-YI; (SAN JOSE,
CA) ; BERESTOV; ALEXANDER; (SAN JOSE, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
SONY CORPORATION |
TOKYO |
|
JP |
|
|
Family ID: |
59496423 |
Appl. No.: |
15/016936 |
Filed: |
February 5, 2016 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06T 7/80 20170101; H04N
13/246 20180501; H04N 17/002 20130101 |
International
Class: |
G06T 7/00 20060101
G06T007/00; H04N 5/04 20060101 H04N005/04 |
Claims
1. A system for camera calibration, comprising: at least one
circuit in a first electronic device configured to: determine a
first rotation pattern of a three-dimensional (3-D) calibration
object based on a set of images, wherein the set of images
comprises a two dimensional (2-D) texture pattern captured at a
plurality of viewing angles; and communicate control information to
a second electronic device associated with said 3-D calibration
object to rotate said 3-D calibration object, wherein said
communicated control information is based on said determined first
rotation pattern, and wherein a plurality of image frames of said
3-D calibration object are captured to calibrate one of intrinsic
camera parameters or extrinsic camera parameters of said first
electronic device.
2. The system according to claim 1, wherein said first electronic
device is one of an imaging device that captures said plurality of
image frames of said 3-D calibration object or a computing device
communicatively coupled to a plurality of imaging devices.
3. The system according to claim 1, wherein said second electronic
device is configured to rotate said 3-D calibration object on a
horizontal axis or a vertical axis based on at least one of receipt
of said communicated control information from said first electronic
device or information stored at said second electronic device.
4. The system according to claim 1, wherein said at least one
circuit is further configured to estimate an angle at which said
first electronic device requires to capture said plurality of image
frames of said 3-D calibration object for said calibration of one
of said intrinsic camera parameters or said extrinsic camera
parameters, wherein said first electronic device is an imaging
device.
5. The system according to claim 1, wherein said at least one
circuit is further configured to receive position information of a
plurality of imaging devices to estimate angles at which each of
said plurality of imaging devices requires to capture said
plurality of image frames of said 3-D calibration object for said
calibration of one of said intrinsic camera parameters or said
extrinsic camera parameters of said plurality of imaging devices,
wherein said first electronic device is a computing device.
6. The system according to claim 1, wherein said 3-D calibration
object comprises at least one facade, wherein said at least one
facade includes at least one of a unique identifier or said 2-D
texture pattern.
7. The system according to claim 6, wherein said at least one
circuit is further configured to detect said unique identifier and
said 2-D texture pattern in each of said captured plurality of
image frames.
8. The system according to claim 1, wherein said at least one
circuit is further configured to receive said captured plurality of
image frames of said 3-D calibration object from each of a
plurality of imaging devices, wherein said plurality of image
frames are captured by each of said plurality of imaging devices
positioned around said 3-D calibration object for parallel
computation of said calibration of one of said intrinsic camera
parameters or said extrinsic camera parameters of said plurality of
imaging devices.
9. The system according to claim 1, wherein said at least one
circuit is further configured to capture said plurality of image
frames of said 3-D calibration object at different rotation states
of said 3-D calibration object for said calibration of one of said
intrinsic camera parameters or said extrinsic camera parameters of
said first electronic device.
10. The system according to claim 1, wherein said at least one
circuit is further configured to determine a similarity related to
distribution of a plurality of feature points between each of said
captured plurality of image frames and one of said set of
images.
11. The system according to claim 10, wherein said at least one
circuit is further configured to select an image frame from said
captured plurality of image frames based on said determined
similarity for said calibration of said intrinsic camera parameters
of said first electronic device.
12. The system according to claim 1, wherein said at least one
circuit is further configured to determine second rotation pattern
of said 3-D calibration object for said calibration of said
extrinsic camera parameters for said first electronic device.
13. The system according to claim 12, wherein said at least one
circuit is further configured to synchronize a time of said capture
of said plurality of image frames of said 3-D calibration object to
each rotation state of said 3-D calibration object at an angle
based on one of said determined first rotation pattern or said
determined second rotation pattern.
14. The system according to claim 13, wherein said at least one
circuit is further configured to determine a 2-D to 3-D mapping of
each image frame of said captured plurality of image frames for
said calibration of said extrinsic camera parameters for said first
electronic device, based on said synchronization, said calibrated
camera intrinsic parameters, and 3-D world coordinates of a
plurality of feature points on said 3-D calibration object.
15. A method for camera calibration, comprising: determining, by at
least one circuit in a first electronic device, a first rotation
pattern of a three-dimensional (3-D) calibration object based on a
set of images comprising a two dimensional (2-D) texture pattern
captured at a plurality of viewing angles; and communicating, by
said at least one circuit, control information to a second
electronic device associated with said 3-D calibration object to
rotate said 3-D calibration object, wherein said communicated
control information is based on said determined first rotation
pattern, and wherein a plurality of image frames of said 3-D
calibration object are captured to calibrate one of intrinsic
camera parameters or extrinsic camera parameters of said first
electronic device.
16. The method according to claim 15, further comprising detecting,
by said at least one circuit, a unique identifier and a texture
pattern in each of said captured plurality of image frames.
17. The method according to claim 15, further comprising
determining, by said at least one circuit, a similarity related to
distribution of a plurality of feature points between each of said
captured plurality of image frames and one of said set of
images.
18. The method according to claim 17, further comprising selecting,
by said at least one circuit, an image frame from said captured
plurality of image frames based on said determined similarity for
said calibration of said intrinsic camera parameters of said first
electronic device.
19. The method according to claim 15, further comprising
determining, by said at least one circuit, a second rotation
pattern of said 3-D calibration object for said calibration of said
extrinsic camera parameters of said first electronic device.
20. The method according to claim 19, further comprising
synchronizing, by said at least one circuit, a time of said capture
of said plurality of image frames of said 3-D calibration object to
each rotation state of said 3-D calibration object at an angle,
based on said determined first rotation pattern or said determined
second rotation pattern.
21. The method according to claim 20, further comprising
determining, by said at least one circuit, a 2-D to 3-D mapping of
each image frame of said captured plurality of image frames for
said calibration of said extrinsic camera parameters for said first
electronic device, based on said synchronization, said calibrated
camera intrinsic parameters, and 3-D world coordinates of a
plurality of feature points on said 3-D calibration object.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS/INCORPORATION BY
REFERENCE
[0001] None.
FIELD
[0002] Various embodiments of the disclosure relate to a system and
method for camera calibration. More specifically, various
embodiments of the disclosure relate to system and method for
camera calibration by use of a rotatable three-dimensional (3-D)
calibration object.
BACKGROUND
[0003] Geometric camera calibration is a technique that estimates
various parameters of a lens and image sensors of an
image-capturing device, such as a camera. Usually, such parameters
may refer to intrinsic and extrinsic camera parameters and
distortion coefficients. Currently, the time required to calibrate
intrinsic parameters of a camera may be proportional to the number
of cameras in an imaging environment. This may involve manual
capture of several images and computation of the intrinsic
parameters by each camera in turns. Calibration of the extrinsic
parameters may also depend on the intrinsic parameters. Thus,
conventional camera calibration techniques for the intrinsic and/or
extrinsic camera parameters may be a time-consuming process.
[0004] In certain scenarios, intrinsic and/or extrinsic camera
parameter estimation techniques may employ a fixed two-dimensional
(2-D) calibration object or texture pattern. In such scenarios, the
position of each camera may be restricted by a viewing angle so
that the texture pattern is discernible by the cameras. In certain
other scenarios, camera extrinsic parameter estimation techniques
may employ a three-dimensional (3-D) calibration object. A
perspective distortion may make feature point detection and precise
camera positioning more difficult. Thus, an advanced system and/or
technique may be required for a quick and automated calibration of
intrinsic and/or extrinsic camera parameters of one or more
cameras, with increased accuracy.
[0005] Further limitations and disadvantages of conventional and
traditional approaches will become apparent to one of skill in the
art, through comparison of described systems with some aspects of
the present disclosure, as set forth in the remainder of the
present application and with reference to the drawings.
SUMMARY
[0006] A system and a method are provided for camera calibration by
use of a rotatable three-dimensional (3-D) calibration object
substantially as shown in, and/or described in connection with, at
least one of the figures, as set forth more completely in the
claims.
[0007] These and other features and advantages of the present
disclosure may be appreciated from a review of the following
detailed description of the present disclosure, along with the
accompanying figures, in which like reference numerals refer to
like parts throughout.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] FIG. 1A is a block diagram that illustrates a network
environment for camera calibration by use of a rotatable 3-D
calibration object, in accordance with an embodiment of the
disclosure.
[0009] FIG. 1B is a block diagram that illustrates another network
environment for camera calibration by use of a rotatable 3-D
calibration object, in accordance with an embodiment of the
disclosure.
[0010] FIG. 2 illustrates a block diagram of an exemplary
electronic device for camera calibration by use of a rotatable 3-D
calibration object, in accordance with an embodiment of the
disclosure.
[0011] FIG. 3A and 3B, collectively, illustrate an exemplary
scenario for implementation of the disclosed system and method for
camera calibration by use of a rotatable 3-D calibration object, in
accordance with an embodiment of the disclosure.
[0012] FIGS. 4A and 4B, collectively, illustrate a first flow chart
for implementation of an exemplary method for camera calibration by
use of a rotatable 3-D calibration object, in accordance with an
embodiment of the disclosure.
[0013] FIGS. 5A and 5B, collectively, illustrate a second flow
chart for implementation of an exemplary method for camera
calibration by use of a rotatable 3-D calibration object, in
accordance with an embodiment of the disclosure.
[0014] FIG. 6 illustrates a third flow chart related to a rotation
pattern determined for calibration of intrinsic camera parameters
for implementation of an exemplary method for camera calibration by
use of a rotatable 3-D calibration object, in accordance with an
embodiment of the disclosure.
[0015] FIG. 7 illustrates a fourth flow chart related to another
rotation pattern determined for calibration of extrinsic camera
parameters for implementation of an exemplary method for camera
calibration by use of a rotatable 3-D calibration object, in
accordance with an embodiment of the disclosure.
DETAILED DESCRIPTION
[0016] The following described implementations may be found in the
disclosed system and method for camera calibration by use of a
rotatable three-dimensional (3-D) calibration object. Exemplary
aspects of the disclosure may include a first electronic device,
which may determine a rotation pattern of a three-dimensional (3-D)
calibration object. The rotation pattern may be determined based on
a set of pre-selected images. The set of pre-selected images may
include a two-dimensional (2-D) texture pattern captured at
pre-defined viewing angles. Control information may be communicated
to a second electronic device associated with the 3-D calibration
object. The control information may be communicated to rotate the
3-D calibration object in accordance with the determined rotation
pattern. A plurality of image frames of the 3-D calibration object
may be captured to calibrate intrinsic and/or extrinsic camera
parameters of the first electronic device.
[0017] In accordance with an embodiment, the first electronic
device may correspond to an imaging device that may capture the
plurality of image frames of the 3-D calibration object. In
accordance with an embodiment, the first electronic device may
correspond to a computing device that may be communicatively
coupled to a plurality of imaging devices.
[0018] In accordance with an embodiment, the second electronic
device may be configured to rotate the 3-D calibration object on
horizontal and/or vertical axes. The rotation may be based on
receipt of the communicated control information from the first
electronic device, or pre-stored control information at the second
electronic device.
[0019] In accordance with an embodiment, the required angle at
which the first electronic device may capture the plurality of
image frames of the 3-D calibration object may be determined. In
such an embodiment, the first electronic device may be the imaging
device. The angle may be determined for calibration of the
intrinsic and/or the extrinsic camera parameters.
[0020] In accordance with an embodiment, position information of a
plurality of imaging devices may be received. In such an
embodiment, the first electronic device may be the computing
device. The position information of the plurality of imaging
devices may be used to determine an angle at which each of the
plurality of imaging devices requires the capture of the plurality
of image frames of the 3-D calibration object for the calibration
of the intrinsic and/or the extrinsic camera parameters of the
plurality of imaging devices.
[0021] In accordance with an embodiment, the 3-D calibration object
may include one or more facades. Each facade of the one or more
facades may include a unique identifier at a pre-defined position
and/or a pre-defined texture pattern that may correspond to the 2-D
texture pattern. A plurality of feature points may be detected in
each of the captured plurality of image frames. The plurality of
feature points may correspond to the unique identifier and/or the
pre-defined texture pattern of the 3-D calibration object.
[0022] In accordance with an embodiment, the captured plurality of
image frames of the 3-D calibration object may be received from
each of the plurality of imaging devices. The plurality of image
frames may be captured by each of the plurality of imaging devices
for parallel computation of the calibration of the intrinsic and/or
the extrinsic camera parameters of the plurality of imaging
devices. The plurality of imaging devices may be positioned around
the 3-D calibration object.
[0023] In accordance with an embodiment, the plurality of image
frames of the 3-D calibration object may be captured at different
rotation states of the 3-D calibration object for the calibration
of the intrinsic and/or the extrinsic camera parameters of the
first electronic device. In accordance with an embodiment, a
similarity related to distribution of a plurality of feature points
between each of the captured plurality of image frames, and at
least one of the set of pre-selected images, may be determined.
[0024] In accordance with an embodiment, an image frame from the
captured plurality of image frames may be selected. The selection
may be based on the determined similarity for the calibration of
the intrinsic camera parameters of the first electronic device. In
accordance with an embodiment, another rotation pattern of the 3-D
calibration object may be determined for the calibration of the
extrinsic camera parameters for the first electronic device.
[0025] In accordance with an embodiment, a time-of-capture of the
plurality of image frames of the 3-D calibration object may be
synchronized to each rotation state of the 3-D calibration object
at a specific angle. The synchronization may be based on the
determined rotation pattern and/or other rotation pattern.
[0026] In accordance with an embodiment, a 2-D to 3-D mapping of
each image frame of the captured plurality of image frames may be
determined for the calibration of the extrinsic camera parameters
for the first electronic device. The 2-D to 3-D mapping may be
determined based on the synchronization, the estimated camera
intrinsic parameters, and pre-stored 3-D world coordinates of the
plurality of feature points on the 3-D calibration object.
[0027] FIG. 1A is a block diagram that illustrates a network
environment for camera calibration by use of a rotatable
three-dimensional calibration object, in accordance with an
embodiment of the disclosure. With reference to FIG. 1A, there is
shown an exemplary network environment 100A. The network
environment 100A may include a first electronic device 102, a
second electronic device 104, a three-dimensional (3-D) calibration
object 106, a communication network 108, and one or more users,
such as a user 110. The first electronic device 102 may be
communicatively coupled to the second electronic device 104, via
the communication network 108. The second electronic device 104 may
be associated with the 3-D calibration object 106. The user 110 may
be associated with the first electronic device 102.
[0028] The first electronic device 102 may comprise suitable logic,
circuitry, interfaces, and/or code that may be configured to
communicate with the second electronic device 104. Examples of the
first electronic device 102 may include, but are not limited to, an
imaging device, such as a camera, a camcorder, an image- or
video-processing device, a motion-capture system, and/or a
projector. In accordance with an embodiment, the first electronic
device 102 may be implemented as a computing device (as described
in FIG. 1B).
[0029] The second electronic device 104 may comprise suitable
logic, circuitry, interfaces, and/or code that may be configured to
receive instructions from the first electronic device 102, via the
communication network 108. The second electronic device 104 may be
configured to rotate the 3-D calibration object 106 in a 3-axes
rotation.
[0030] The 3-D calibration object 106 may have various geometrical
shapes, such as a cube or a polyhedron. The 3-D calibration object
106 may comprise one or more facades with a pre-defined 2-D texture
pattern. In accordance with an embodiment, the one or more facades
may have a same pre-defined texture pattern. The pre-defined
texture pattern may be a homogenous or a heterogeneous texture
pattern. In accordance with an embodiment, certain facades may have
the same pre-defined texture pattern, whereas certain other facades
of the 3-D calibration object 106 may have a different pre-defined
texture pattern. In accordance with an embodiment, based on an
implementation requirement, a single facade may be the same or
different 2-D texture pattern. An example of the 3-D calibration
object 106 is shown in FIG. 1B, where the 3-D calibration object
106 includes four facades with homogenous shape and homogenous 2-D
texture pattern, and two facades devoid of the 2-D texture
pattern.
[0031] In accordance with an embodiment, in addition to the
pre-defined texture pattern, each facade may also include a unique
identifier at a pre-defined position of the facade. For instance,
the unique identifier may be a colored mark or other unique mark,
positioned at a unique region of each facade. The unique identifier
may be positioned such that the detection of the plurality of
feature points on each facade may not be affected. The 3-D
calibration object 106 may be rotatable in a 3-axes rotation by the
second electronic device 104.
[0032] The communication network 108 may include a medium through
which the first electronic device 102 and the second electronic
device 104, may communicate with each other. The communication
network 108 may be a wired or wireless communication network.
Examples of the communication network 108 may include, but are not
limited to, a Local Area Network (LAN), a Wireless Local Area
Network (WLAN), a cloud network, a Long Term Evolution (LTE)
network, a plain old telephone service (POTS), a Metropolitan Area
Network (MAN), and/or the Internet. Various devices in the network
environment 100A may be configured to connect to the communication
network 108, in accordance with various wired and wireless
communication protocols. Examples of such wired and wireless
communication protocols may include, but are not limited to,
Transmission Control Protocol and Internet Protocol (TCP/IP), User
Datagram Protocol (UDP), Hypertext Transfer Protocol (HTTP), File
Transfer Protocol (FTP), ZigBee, EDGE, infrared (IR), IEEE 802.11,
802.16, Long Term Evolution (LTE), Light Fidelity (Li-Fi), and/or
other cellular communication protocols or Bluetooth (BT)
communication protocols.
[0033] In accordance with an embodiment, the first electronic
device 102 may be an imaging device to be calibrated. The first
electronic device 102 may be configured to capture a plurality of
images of a pre-defined 2-D texture pattern, with different viewing
angles. For instance, at +45.degree., +30.degree., 0.degree.,
-30.degree., -45.degree. horizontal orientation, and -15.degree.,
0.degree., +15.degree. vertical orientation (or tilt angle), the
plurality of images may be captured as candidate images from
pre-specified position(s) (such as known real-world coordinates) of
the first electronic device 102. The plurality of images may be
candidate images to learn certain images for calibration of
intrinsic camera parameters.
[0034] In accordance with an embodiment, the first electronic
device 102 may be configured to select certain images from the
captured plurality of images taken at different viewing angles. In
accordance with an embodiment, a set of selected images from the
captured plurality of images may represent best shots as compared
to others of the candidate images. The set of the selected images
may be referred to as a learned image set. The set of the selected
images may represent a high accuracy of intrinsic calibration
results, as compared to others of the candidate images. The initial
capture of the plurality of images and the preparation of the set
of the selected images (or the learned image set) may be a one-time
activity.
[0035] In operation, the first electronic device 102, or a new
imaging device that is to be calibrated, may be placed at a fixed
position so that during calibration the first electronic device 102
or the new electronic device may not need to be moved. In
accordance with an embodiment, the first electronic device 102 may
be configured to receive its position information. The position
information of the first electronic device 102 may be used to
estimate the required angle at which the first electronic device
102 needs to be in order to capture a plurality of images of the
3-D calibration object 106, for the calibration of the intrinsic
and/or the extrinsic camera parameters.
[0036] In accordance with an embodiment, the first electronic
device 102 may be configured to determine a rotation pattern of the
3-D calibration object 106. The rotation pattern may be determined
based on a set of pre-selected images that includes the pre-defined
2-D texture pattern captured at pre-defined viewing angles. The set
of pre-selected images may correspond to the learned image set (as
described above).
[0037] In accordance with an embodiment, the first electronic
device 102 may be configured to communicate control information to
the second electronic device 104, associated with the 3-D
calibration object 106. Based on the control information received
from the first electronic device 102, the second electronic device
104 may rotate the 3-D calibration object 106, in accordance with
the determined rotation pattern. The control information may
correspond to the determined rotation pattern. The 3-D calibration
object 106 may be rotated on horizontal and vertical axes, based
upon receipt of the communicated control information.
[0038] In accordance with an embodiment, the first electronic
device 102 may be configured to capture a video or a plurality of
image frames of the 3-D calibration object 106, in accordance with
the determined rotation pattern. In accordance with an embodiment,
the rotation of the 3-D calibration object 106 by the second
electronic device 104, may be intermittent and not continuous, such
that the first electronic device 102 may have a clear shot of the
facades of the 3-D calibration object 106.
[0039] In accordance with an embodiment, each facade of the 3-D
calibration object 106 may have a detectable 2-D texture pattern
that may be a homogenous or a heterogeneous texture pattern. The
texture pattern may indicate a plurality of feature points.
Further, in addition to the texture pattern, each facade may also
include a unique identifier at a pre-defined position of the
facade. For instance, the unique identifier may be a colored mark
or other unique mark positioned at a specific region of each
facade. The unique identifier may be positioned such that the
detection of the plurality of feature points on each facade during
image processing is not affected.
[0040] In accordance with an embodiment, the first electronic
device 102 may be configured to detect a plurality of feature
points in each of the captured plurality of image frames. The
plurality of feature points may correspond to the 2-D texture
pattern and/or the unique identifier on at least one facade of the
3-D calibration object 106. For instance, in a chessboard pattern,
corners of the chessboard pattern in each facade may correspond to
the plurality of feature points that may be detected (FIG. 3B).
Notwithstanding, other known two-dimensional (2-D) patterns, such
as circle patterns (FIG. 1B), symmetric, or asymmetric patterns,
may be used for easy detection of the plurality of feature
points.
[0041] In accordance with an embodiment, the first electronic
device 102 may be configured to match the distribution of the
plurality of feature points between an image frame of the captured
plurality of image frames and an image of the set of pre-selected
images. A similarity related to distribution of plurality of
feature points may be determined between an image frame of the
captured plurality of image frames and an image of the set of
pre-selected images.
[0042] In accordance with an embodiment, the first electronic
device 102 may be configured to select certain image frames from
the captured plurality of image frames, based on the determined
similarity for calibration of intrinsic camera parameters of the
first electronic device 102. The selected image frames may be
referred to as a first set of image frames from the captured
plurality of image frames for intrinsic calibration. The first set
of image frames may be utilized for the estimation of the intrinsic
camera parameters of the first electronic device 102.
[0043] In accordance with an embodiment, the first electronic
device 102 may be configured to determine another rotation pattern
customized for estimation of extrinsic camera parameters. The
second electronic device 104 may be configured to rotate the 3-D
calibration object 106 around its vertical axis at a pre-defined
step angle. The rotation may be programmed and intermittent. The
rotation may occur based on a receipt of other control information
received from the first electronic device 102. The other control
information may correspond to the determined other rotation
pattern.
[0044] In accordance with an embodiment, the first electronic
device 102 may be configured to further capture another plurality
of images or another video of the 3-D calibration object 106, at
different rotation states. The 3-D real-world coordinates of all
the feature points (and/or the unique identifier) on the 3-D
calibration object 106 may be known at all times throughout the
rotation of the 3-D calibration object 106. Accordingly, the
time-of-capture of the plurality of image frames of the 3-D
calibration object 106 may be synchronized to various rotation
states of the 3-D calibration object 106. Such synchronization may
be time-based synchronization based on the determined other
rotation pattern. As an orientation of the facade of the 3-D
calibration object 106 for a time instant in the determined other
rotation pattern becomes known, a 2-D to 3-D mapping may be derived
for an image frame captured at the time instant in the determined
other rotation pattern.
[0045] The first electronic device 102 may be configured to
determine the 2-D to 3-D mapping of each image frame of the
captured other plurality of image frames for the calibration of
extrinsic camera parameters for the first electronic device 102.
Such 2-D to 3-D mapping may be based on the synchronization, the
estimated intrinsic camera parameters, and/or the pre-stored 3-D
world coordinates of the plurality of feature points on the 3-D
calibration object 106. In accordance with an embodiment, a single
rotation pattern may be determined and executed that may include
the rotation pattern for calibration of intrinsic camera parameters
and the other rotation pattern for calibration of extrinsic camera
parameters.
[0046] FIG. 1B is a block diagram that illustrates another network
environment for camera calibration by use of a rotatable 3-D
calibration object, in accordance with an embodiment of the
disclosure. FIG. 1B is explained in conjunction with elements from
FIG. 1A. With reference to FIG. 1B, there is shown an exemplary
network environment 100B. The network environment 100B may include
an apparatus 112 to rotate the 3-D calibration object 106, a
plurality of imaging devices 114A to 114D, the communication
network 108, and one or more users, such as the user 110. The
apparatus 112 may include one or more motors 112A, a stand
mechanism 112B, and a controller 112C. The 3-D calibration object
106 may include a pre-defined 2-D texture pattern 106A and a unique
identifier 106B on one or more facades of the 3-D calibration
object 106.
[0047] The apparatus 112 may be designed to provide a rotatable
base to the 3-D calibration object 106. The apparatus 112 may
correspond to the second electronic device 104. The one or more
motors 112A may be one or more electromechanical devices that may
convert control information to discrete mechanical movements to
rotate the 3-D calibration object 106. The control information may
be received from the controller 112C or from the first electronic
device 102. Examples of the one or more motors 112A may include,
but are not limited to, a stepper motor and a servo motor. In
accordance with an embodiment, the one or more motors 112A may be
powered by one or more batteries (not shown). The apparatus 112 may
further include the stand mechanism 112B, which may be a structure
that may support the 3-D calibration object 106, and maintain
stability during the 3-axes rotation of the 3-D calibration object
106. For instance, the stand mechanism 112B may be a tripod or a
four-legged stand structure.
[0048] The apparatus 112 may further include the controller 112C.
The controller 112C may be implemented based on a number of
processor technologies known in the art. In accordance with an
embodiment, the controller 112C may comprise suitable logic,
circuitry, interfaces, and/or code that may be configured to
receive control information from the first electronic device 102,
by use of a network interface (not shown). The network interface
may communicate with one or more electronic devices, such as the
first electronic device 102, via the communication network 108. The
network interface may communicate under the control of the
controller 112C. In accordance with an embodiment, the controller
112C may be configured to execute a set of pre-stored instructions
to rotate the 3-D calibration object 106. Examples of the
controller 112C may include, but are not limited to, a
microcontroller, a programmable controller station, a Reduced
Instruction Set Computing (RISC) processor, an Application-Specific
Integrated Circuit (ASIC) processor, a Complex Instruction Set
Computing (CISC) processor, a central processing unit (CPU), an
Explicitly Parallel Instruction Computing (EPIC) processor, a Very
Long Instruction Word (VLIW) processor, a microprocessor, and/or
other processors or control circuits.
[0049] The plurality of imaging devices 114A to 114D may comprise
suitable logic, circuitry, interfaces, and/or code that may be
configured to capture a plurality of image frames or video of the
3-D calibration object 106. The plurality of imaging devices 114A
to 114D may be configured to communicate with the first electronic
device 102. Each of the plurality of imaging devices 114A to 114D
may be configured to receive instructions from the first electronic
device 102. Based on the received instructions, the capture of the
plurality of image frames or video of the 3-D calibration object
106 may be initiated or stopped at various rotation states of the
3-D calibration object 106.
[0050] The 3-D calibration object 106 may include the pre-defined
2-D texture pattern 106A and the unique identifier 106B on one or
more facades. An example of the 3-D calibration object 106 is shown
in the FIG. 1B, where the 3-D calibration object 106 is a cube that
includes four vertical facades with the 2-D texture pattern 106A
and the unique identifier 106B. The other two facades are devoid of
the pre-defined 2-D texture pattern 106A. The 2-D texture pattern
106A may be homogenous or heterogeneous pattern. In this case, the
2-D texture pattern 106A may be a 2-D symmetric circle pattern, as
shown. Further, in addition to the pre-defined 2-D texture pattern
106A, each facade (such as the four vertical facades) may also
include the unique identifier 106B at a pre-defined position of the
facade. For instance, the unique identifier 106B may be a colored
mark or other unique mark or pattern positioned at a unique region
of each facade.
[0051] In an implementation, the first electronic device 102 may be
a computing device communicatively coupled to the plurality of
imaging devices 114A to 114D. Each of the plurality of imaging
devices 114A to 114D may be placed at a fixed position so that
during calibration of the plurality of imaging devices 114A to
114D, the plurality of imaging devices 114A to 114D may not need to
be moved.
[0052] Conventional intrinsic camera parameter calibrations may
require the camera or a calibration object to be moved in order to
capture several (such as 10-100) images for calibration, and thus
it may be a time-consuming process. Further, the time required to
calibrate a camera may be proportional to the number of cameras to
be calibrated as conventional intrinsic camera parameters
calibration may involve manual capture of several images, and
computation of the intrinsic parameters by each camera in turns.
Thus, it may be advantageous to have fully-automated intrinsic
and/or extrinsic camera parameters calibration, as described.
[0053] In operation, the first electronic device 102 may be
configured to receive position information of the plurality of
imaging devices 114A to 114D. The position information may be used
to estimate the required angles at which each of the plurality of
imaging devices 114A to 114D needs to be in order to capture a
plurality of image frames of the 3-D calibration object 106, for
the calibration of the intrinsic and/or the extrinsic camera
parameters.
[0054] In accordance with an embodiment, the first electronic
device 102 may be configured to determine a rotation pattern of the
3-D calibration object 106. The rotation pattern may be determined
based on a set of pre-selected images (such as the set of selected
images as described in FIG. 1A). Each image of the set of
pre-selected images may include the pre-defined 2-D texture pattern
106A, captured at pre-defined viewing angles. The rotation pattern
may be designed to generate one or more rotation sequences, such
that each of the plurality of imaging devices 114A to 114D may
capture a plurality of image frames of the 3-D calibration object
106 for intrinsic calibration.
[0055] In accordance with an embodiment, the rotation pattern may
be 3-axes rotation designed such that the captured plurality of
image frames by each of the plurality of imaging devices 114A to
114D may be representative of one or more images of the set of
pre-selected images. The captured plurality of image frames by each
of the plurality of imaging devices 114A to 114D may be a sample
set of images. The set of pre-selected images may correspond to the
learned image set. The use of the learned image set may be
efficient. As long as sufficient sample images are collected that
match the learned image set, the capture and further processing of
the captured plurality of image frames or video may be stopped.
Thus, capture of a large number of image frames or videos for the
calibration may not be required.
[0056] In accordance with an embodiment, one or more rotation
sequences for intrinsic calibration may be designed by use of the
following mathematical expression:
0.ltoreq.n.sub.in.ltoreq.360/(.theta..sub.in.degree..times.P)
(1)
where "n.sub.in" may be a numeric value used for intrinsic
calibration, "P" may be the number of facades of the 3-D
calibration object 106 with pre-defined 2-D texture pattern 106A
and/or a unique identifier 106B, and ".theta..sub.in" may be a
pre-defined step angle used for intrinsic parameter calibration.
The rotation sequence may repeat at a certain degree along the
vertical axis, given by the mathematical expression:
(n.sub.in.times..theta..sub.in+) (2).
In accordance with an embodiment, the smaller the pre-defined step
angle (.theta..degree.), the better sample images may be captured
to match with the learned image set.
[0057] In accordance with the mathematical expressions (1) and (2),
when "n.sub.in"="0", a 3-axes rotation configuration may be
designed for a first image of the set of pre-selected images. In
instances when all the possible rotation configurations for the
first image of the set of pre-selected images are generated, the
numeric value "n.sub.in" may be increased by a value "1" (that is
"n.sub.in=n.sub.in+1"). In instances, when
"n.sub.in">"360/(.theta..sub.in.degree..times.P)", then the
rotation may stop. In instances, when
"n.sub.in".ltoreq."360/(.theta..sub.in.degree..times.P)", then the
3-D calibration object 106 may be rotated along the vertical axis
clockwise by the pre-defined step angle (.theta..sub.in.degree.).
Similarly, a 3-axes rotation may be designed for a next image of
the set of pre-selected images, until a complete rotation pattern
is determined for all images of the set of pre-selected images for
intrinsic camera parameters calibration. The 3-axes rotation may
represent a horizontal and vertical rotation configuration. The
rotation of the 3-D calibration object 106, in accordance with the
determined rotation pattern that may include one or more rotation
sequences, is further explained in FIG. 6.
[0058] In accordance with an embodiment, the first electronic
device 102 may be configured to communicate control information to
the network interface of the apparatus 112, via the communication
network 108. The controller 112C may utilize the communicated
control information to regulate the one or more motors 112A. The
one or more motors 112A may generate mechanical movements to rotate
the 3-D calibration object 106, in accordance with the determined
rotation pattern. The 3-D calibration object 106 may be rotated on
horizontal and vertical axes in a 3-axes rotation, based on the
receipt of the communicated control information.
[0059] In accordance with an embodiment, the first electronic
device 102 may further communicate instructions to the plurality of
the imaging devices 114A to 114D to simultaneously capture a
plurality of image frames of the 3-D calibration object 106, in
accordance with the determined rotation pattern. In accordance with
an embodiment, the plurality of the imaging devices 114A to 114D
may capture videos of the 3-D calibration object 106
simultaneously. In accordance with an embodiment, the rotation of
the 3-D calibration object 106, in accordance with the determined
rotation pattern, may be intermittent and not continuous. The
intermittent rotation may enable the plurality of the imaging
devices 114A to 114D to have a clear shot of the facades of the 3-D
calibration object 106 and to avoid motion blur in the captured
image frames.
[0060] In accordance with an embodiment, for further processing,
the first electronic device 102 may be configured to receive the
captured plurality of image frames or the captured video from each
of the plurality of imaging devices 114A to 114D. The captured
plurality of image frames may include the 3-D calibration object
106. In accordance with an embodiment, each of the videos captured
by the plurality of the imaging devices 114A to 114D may be
processed in parallel by the same device, such as the first
electronic device 102 (when implemented as the computing device).
In accordance with an embodiment, each of the videos captured by
the plurality of the imaging devices 114A to 114D may be processed
by a separate device, such as a plurality of computing devices.
Alternatively, each of the plurality of imaging devices 114A to
114D may process its own captured video or plurality of image
frames simultaneously (when the first electronic device 102 is
implemented as an imaging device, as described in FIG. 1A). Such
processing may be performed for the simultaneous calibration of the
intrinsic camera parameters of the plurality of imaging devices
114A to 114D.
[0061] In accordance with an embodiment, each facade of the 3-D
calibration object 106 may have a detectable texture pattern that
may be a homogenous or heterogeneous texture pattern. In this case,
the pre-defined 2-D texture pattern 106A, such as homogenous circle
pattern on the vertical facades of the 3-D calibration object 106,
is shown in the FIG. 1B. In this case, the unique identifier 106B
is positioned at a corner of each facade with the pre-defined 2-D
texture pattern 106A of the 3-D calibration object 106, as shown in
FIG. 1B. The unique identifier 106B may be positioned such that the
detection of the plurality of feature points on each facade during
image processing may not be affected.
[0062] In accordance with an embodiment, the first electronic
device 102 may be configured to detect a plurality of feature
points in each of the captured plurality of image frames. The
plurality of feature points may correspond to the pre-defined 2-D
texture pattern 106A and the unique identifier 106B. The detection
of the plurality of feature points may be easier as conventional,
flat 2-D texture patterns may be used on each facade of the 3-D
calibration object 106. Notwithstanding, other known
two-dimensional (2-D) patterns, such as chessboard pattern, blob
patterns, symmetric or asymmetric patterns, may be used for simple
detection of the plurality of feature points. In accordance with an
embodiment, the plurality of feature points on each facade that may
be the 2-D texture pattern 106A may be detected by use of known
pattern-detection algorithms. Examples of such 2-D texture
pattern-detection algorithms may include, but are not limited to,
pattern detection algorithms of a "OpenCV" library, such as
"findChess-boardCorners( )" function or "HoughCircles" function, a
Bouguet MatLab Toolbox, and/or other known supervised or
unsupervised algorithms for pattern detection as per the texture
pattern used, in the field of camera calibration.
[0063] In accordance with an embodiment, the first electronic
device 102 may be configured to determine a similarity of
distribution of the plurality of feature points between each image
frame of the captured plurality of image frames and an image of the
set of pre-selected images. The first electronic device 102 may be
configured to select the image frames from the captured plurality
of image frames that have feature point distributions similar to
one of the images in the set of pre-selected images. In instances,
when all images in the set of pre-selected images match certain
image frames from the captured plurality of image frames, the
dynamic detection and selection process may stop. Thus, the use of
the learned image set, such as the set of pre-selected images, may
increase efficiency as it may not require capture of a large number
of images or videos for intrinsic calibration.
[0064] In accordance with an embodiment, when all images in the set
of pre-selected images are matched with certain image frames from
the captured plurality of image frames, intrinsic camera parameters
may be estimated for each of the plurality of imaging devices 114A
to 114D. In accordance with an embodiment, one or more conventional
intrinsic parameter estimation techniques may then be easily
applied.
[0065] In accordance with an embodiment, the first electronic
device 102 may be configured to determine another rotation pattern
customized for extrinsic parameter calibration. The other rotation
pattern determined for calibration of extrinsic camera parameters
may be different from the rotation pattern determined for the
calibration of intrinsic camera parameters. The 3-D calibration
object 106 may be rotated around its vertical axis in the other
rotation pattern which may be customized for the extrinsic
parameter calibration.
[0066] In accordance with an embodiment, a rotation sequence for
extrinsic parameters calibration may be designed by use of the
following mathematical expression:
0.ltoreq.n.sub.ex.ltoreq.360/(.theta..sub.ex.degree..times.P)
(3),
where, "n.sub.ex" is an integer, "P" is the number of facades of
the 3-D calibration object 106, and ".theta..sub.ex.degree. " is a
pre-defined step angle for extrinsic parameters calibration. In
accordance with an embodiment, the other pre-defined step angle
".theta..sub.ex.degree." for extrinsic parameters calibration may
be greater than the pre-defined step angle ".theta..sub.in.degree."
for intrinsic parameters calibration (that is,
".theta..sub.ex.degree.">".theta..sub.in.degree."). In
accordance with an embodiment, the 3-D calibration object 106 may
be rotated at all of the following degrees along the vertical axis,
given by the mathematical expression:
n.sub.ex.times..theta..sub.ex.degree. (4).
[0067] In accordance with the mathematical expressions (3) and (4),
when "n.sub.ex"="0", at a first rotation state of the 3-D
calibration object 106, the rotation may temporarily stop for a
pre-defined duration, which may be referred to as the capturing
period. In a first capturing period, the plurality of the imaging
devices 114A to 114D may capture another plurality of images or
video of the 3-D calibration object 106 in the rotation state of
the 3-D calibration object 106. After the first capturing period,
the value of the integer "n.sub.ex" may be increased by a numeric
value "1" (that is, "n.sub.ex"="n.sub.ex+1"). In instances when
"n.sub.ex>"360/(.theta..sub.ex.degree..times.P)", the rotation
may stop. In instances when
"n.sub.in".ltoreq."360/(.theta..sub.ex.degree..times.P)", the 3-D
calibration object 106 may be rotated along the vertical axis
clockwise by the other pre-defined step angle
".theta..sub.ex.degree.". Accordingly, the integer value may be
then set to "n=1", at a second rotation state of the 3-D
calibration object 106. Again, the rotation may temporarily stop
for the pre-defined duration, which may be the second capturing
period. The rotation of the 3-D calibration object 106, in
accordance with the determined other rotation pattern that may
include one or more rotation sequences for calibration of extrinsic
camera parameters, is further explained in FIG. 7.
[0068] The controller 112C may be configured to generate a
timestamp for each rotation state of the 3-D calibration object
106. Accordingly, the time-of-capture of the plurality of image
frames, during the various capturing periods, by each of the
plurality of the imaging devices 114A to 114D may be associated to
the rotation state of the 3-D calibration object 106. In accordance
with an embodiment, at each pre-defined step angle, the first
electronic device 102 may be configured to synchronize
time-of-capture of the plurality of image frames of the 3-D
calibration object 106 with the rotation state of the 3-D
calibration object 106. Such synchronization may be based on the
association of the timestamps and/or the determined other rotation
pattern.
[0069] The 3-D real-world coordinates of all the feature points and
the unique identifier on the 3-D calibration object 106 are known
at all times throughout the rotation of the 3-D calibration object
106. The orientation of a facade of the 3-D calibration object 106
for a time instance may be known in the determined other rotation
pattern. Accordingly, a two-dimensional (2-D) to 3-D mapping for an
image frame captured at the time instant in the determined rotation
pattern may be derivable. The first electronic device 102 may be
configured to determine the 2-D to 3-D mapping of each image frame
of the captured other plurality of image frames for the calibration
of extrinsic camera parameters for the plurality of the imaging
devices 114A to 114D. Such 2-D to 3-D mapping may be based on the
synchronization, the calibrated camera intrinsic parameters, and
the 3-D world coordinates of the plurality of feature points on the
3-D calibration object 106. During the extrinsic calibration, the
plurality of imaging devices 114A to 114D may capture multiple
perspectives of the homogeneous 2-D pattern, which makes the
resultant accuracy more uniform among different viewing angles.
[0070] Certain conventional camera extrinsic parameter estimations
with calibration objects/pattern may use fixed 2-D texture
patterns. In such cases, the positions of imaging devices may be
restricted by viewing angles in which the imaging devices may
discern the pattern. Such angles are usually less than "160
degrees" in front of the calibration pattern. The disclosed system
and method for camera calibration, by use of the rotatable 3-D
calibration object 106, does not impose any limitation of viewing
angles. As a result, the plurality of imaging devices 114A to 114D
may be positioned around the 3-D calibration object 106, where the
pre-defined 2-D texture pattern 106A of the rotatable 3-D
calibration object 106 may be discernible by the imaging devices
114A to 114D with viewing angles of full "360 degree".
[0071] In accordance with an embodiment, the plurality of feature
points, which may include the unique identifier 106B, may be
aggregated for each of the plurality of imaging devices 114A to
114D from the captured plurality of image frames for extrinsic
camera parameter estimation. In accordance with an embodiment, the
extrinsic camera parameters may be estimated for each of the
plurality of the imaging devices 114A to 114D. In accordance with
an embodiment, one or more conventional extrinsic camera parameter
estimation techniques may be then easily applied based on the 2-D
to 3-D mapping.
[0072] FIG. 2 illustrates a block diagram of an exemplary
electronic device for camera calibration by use of a rotatable 3-D
calibration object, in accordance with an embodiment of the
disclosure. FIG. 2 is explained in conjunction with elements from
FIG. 1A and FIG. 1B. With reference to FIG. 2, there is shown the
first electronic device 102. The first electronic device 102 may
comprise one or more processors, such as a processor 202, a memory
204, one or more input/output (I/O) devices, such as an I/O device
206, a sensing device 208, and a network interface 210.
[0073] The processor 202 may be communicatively coupled to the
memory 204, the I/O device 206, and the network interface 210. The
network interface 210 may communicate with the second electronic
device 104 (FIG. 1A), via the communication network 108, under the
control of the processor 202. The network interface 210 may
communicate with the network interface of the apparatus 112 (FIG.
1B), via the communication network 108, under the control of the
processor 202.
[0074] The processor 202 may comprise suitable logic, circuitry,
interfaces, and/or code that may be configured to execute a set of
instructions stored in the memory 204. The processor 202 may be
implemented based on a number of processor technologies known in
the art. Examples of the processor 202 may be an X86-based
processor, X86-64-based processor, a Reduced Instruction Set
Computing (RISC) processor, an Application-Specific Integrated
Circuit (ASIC) processor, a Complex Instruction Set Computing
(CISC) processor, a central processing unit (CPU), an Explicitly
Parallel Instruction Computing (EPIC) processor, a Very Long
Instruction Word (VLIW) processor, and/or other processors or
circuits.
[0075] The memory 204 may comprise suitable logic, circuitry,
and/or interfaces that may be configured to store a machine code
and/or a set of instructions executable by the processor 202. The
memory 204 may be further configured to store operating systems and
associated applications. Examples of implementation of the memory
204 may include, but are not limited to, Random Access Memory
(RAM), Read Only Memory (ROM), Electrically Erasable Programmable
Read-Only Memory (EEPROM), Hard Disk Drive (HDD), a Solid-State
Drive (SSD), a CPU cache, and/or a Secure Digital (SD) card.
[0076] The I/O device 206 may comprise suitable logic, circuitry,
interfaces, and/or code that may be configured to receive an input
from the user 110. The I/O device 206 may be further configured to
provide an output to the user 110. The I/O device 206 may comprise
various input and output devices that may be operable to
communicate with the processor 202. Examples of the input devices
may include, but are not limited to, an image-capturing unit (not
shown), a camcorder, a touch screen, a keyboard, a mouse, a
joystick, a microphone, a motion sensor, a light sensor, and/or a
docking station. Examples of the output devices may include, but
are not limited to, a display screen, a projector screen, and/or a
speaker.
[0077] The sensing device 208 may comprise suitable logic,
circuitry, and/or interfaces that may be operable to store a
machine code and/or a computer program with at least one code
section executable by the processor 202. The sensing device 208 may
further comprise one or more sensors to capture of the plurality of
image frames and/or videos, by the image capturing unit. The one or
more sensors may further include a microphone to detect a voice
pattern, confirm recognition, identification, and/or verification
of the user 110. Examples of the one or more sensors may include,
but are not limited to, an image sensor, a global positioning
system (GPS) sensor, a compass or magnometer, an ambient light
sensor, a tricorder, a gyroscope, a proximity sensor, a lux meter,
a touch sensor, an infrared sensor, and/or other sensors.
[0078] The network interface 210 may comprise suitable logic,
circuitry, interfaces, and/or code that may be configured to
communicate with the second electronic device 104, via the
communication network 108 (as shown in FIG. 1A). The network
interface 210 may implement known technologies to support wired or
wireless communication of the first electronic device 102 with the
communication network 108. The network interface 210 may include,
but is not limited to, an antenna, a radio frequency (RF)
transceiver, one or more amplifiers, a tuner, one or more
oscillators, a digital signal processor, a coder-decoder (CODEC)
chipset, a subscriber identity module (SIM) card, and/or a local
buffer. The network interface 210 may communicate via wired or
wireless communication with the communication network 108. The
wireless communication may use one or more of the communication
standards, protocols and technologies, such as Global System for
Mobile Communications (GSM), Enhanced Data GSM Environment (EDGE),
wideband code division multiple access (W-CDMA), code division
multiple access (CDMA), time division multiple access (TDMA),
Bluetooth, Long-Term Evolution(LTE), Wireless Fidelity (Wi-Fi)
(such as IEEE 802.11a, IEEE 802.11b, IEEE 802.11g and/or IEEE
802.11n), Light-Fidelity (Li-Fi), voice over Internet Protocol
(VoIP), Wi-MAX, a protocol for email, instant messaging, and/or
Short Message Service (SMS).
[0079] In operation, the processor 202 may be configured to
determine a rotation pattern of the 3-D calibration object 106. The
rotation pattern may be determined based on a set of pre-selected
images. The set of pre-selected images may include a detectable 2-D
texture pattern captured at pre-defined viewing angles. The set of
pre-selected images may correspond to the learned image set. The
determined rotation pattern may be stored as control information in
the memory 204.
[0080] In accordance with an embodiment, the processor 202 may be
configured to communicate control information to the second
electronic device 104, by use of the network interface 210. In
accordance with an embodiment, the second electronic device 104 may
correspond to the apparatus 112. Based on the control information
received from the processor 202, the second electronic device 104
may rotate the 3-D calibration object 106, in accordance with the
determined rotation pattern. The control information may correspond
to the determined rotation pattern. The 3-D calibration object 106
may be rotated on horizontal and vertical axes, based on the
receipt of the communicated control information. In accordance with
an embodiment, the functionalities or operations performed by the
first electronic device 102, as described in FIGS. 1A and 1B, may
performed by the processor 202. Other operations performed by the
processor 202 may be understood from the description in the FIGS.
3A, 3B, 4A, 4B, 5A and 5B.
[0081] FIGS. 3A and 3B, collectively, illustrate an exemplary
scenario for implementation of the disclosed system and method for
camera calibration by use of a rotatable 3-D calibration object, in
accordance with an embodiment of the disclosure. FIG. 3A is
described in conjunction with FIGS. 1A, 1B, and 2. With reference
to FIG. 3A, there is shown a set of candidate images 302 of a 2-D
chessboard pattern, captured at different viewing angles. The set
of candidate images 302 may include a first subset of images 302A,
a second subset of images 302B, and a third subset of images
302C.
[0082] In accordance with the exemplary scenario, the set of
candidate images 302 may correspond to the initial capture of the
plurality of images of the 3-D calibration object 106, from which
the learned set of images is selected (FIG. 1A). The first subset
of images 302A may include views of a 2-D texture pattern, such as
a chessboard texture pattern, in different orientation (or tilt)
angles. The first subset of images 302A may be captured at
"+45.degree.", "+30.degree.", "0.degree.", "-30.degree.", and
"-45.degree." horizontal orientation tilt, and "-15.degree.",
"0.degree.", "+15.degree." vertical orientation tilt that
corresponds to the viewing angles (tilt angles) of a camera (not
shown) with respect to the 2-D texture pattern. The camera may
correspond to one of the plurality of imaging devices 114A to 114D.
The second subset of images 302B may include views of the 2-D
texture pattern rotated at different angles, as shown. The third
subset of images 302C may include views of the 2-D texture pattern
located at different border regions of the images, as shown.
[0083] In accordance with an embodiment, certain images for
intrinsic calibration, such as a set of eleven images, may be
selected from the set of candidate images 302. The set of eleven
images that may be selected by a user, such as the user 110, may
represent the best image set for intrinsic calibration. The
selected set of eleven images may be referred to as a learned image
set. The selected set of eleven images may include an image (shown
encircled by a dashed ellipse) from the first subset of images
302A. The selected set of eleven images may further include all six
images from the second subset of images 302B. The selected set of
eleven images may further include all four images from the third
subset of images 302C.
[0084] With reference to FIG. 3B, there is shown a plurality of
cameras 304A to 304D, a computing device 306, a 2-D chessboard
pattern 308A, a colored unique identifier 308B, the 3-D calibration
object 106, the second electronic device 104, and the apparatus
112. In accordance with the first exemplary scenario, the plurality
of cameras 304A to 304D may correspond to the plurality of imaging
devices 114A to 114D (FIG. 1B). The computing device 306 may
correspond to the first electronic device 102 (FIG. 1B). Further,
the 2-D chessboard pattern 308A and the colored unique identifier
308B may correspond to the 2-D texture pattern 106A (FIG. 1B) and
the unique identifier 106B (FIG. 1B), respectively. The second
electronic device 104 may include the network interface and the
controller 112C (FIG. 1B).
[0085] In accordance with an embodiment, the computing device 306
may be configured to dynamically select certain images from the set
of candidate images 302. The selected set of images may represent a
high accuracy of intrinsic calibration results as compared to other
images of the set of candidate images 302. In accordance with an
embodiment, the selection may be based on a quality threshold
associated with detection of the plurality of feature points in the
set of candidate images 302. The selected set of images may
correspond to a learned set of images.
[0086] In accordance with the exemplary scenario, the plurality of
cameras 304A to 304D may be newly manufactured cameras that require
calibration of intrinsic and extrinsic camera parameters. In
another example, the plurality of cameras 304A to 304D may need to
be installed at a sports field to record a professional sports
event. Thus, the plurality of cameras 304A to 304D may require
uniform intrinsic and extrinsic camera parameter calibrations to be
able to produce uniform results for the professional sports event
recording.
[0087] In accordance with an embodiment, the computing device 306
may be configured to determine a rotation pattern of the 3-D
calibration object 106, for calibration of intrinsic camera
parameters of the plurality of cameras 304A to 304D. The rotation
pattern may be determined based on the set of selected images. The
3-D calibration object 106 may be rotatable and may include four
vertical facades with the same 2-D chessboard pattern 308A and the
colored unique identifier 308B. The plurality of cameras 304A to
304D may be positioned around the 3-D calibration object 106. The
2-D chessboard pattern 308A of the rotatable 3-D calibration object
106 may be discernible by the plurality of cameras 304A to 304D,
with viewing angles of full 360 degrees. As four facades are
utilized, the 3-D calibration object 106 may not be required to be
rotated to full "360 degrees". A "90 degree" rotation of the 3-D
calibration object 106 may have a similar effect of "360 degree"
coverage to generate various viewing angles for the plurality of
cameras 304A to 304D.
[0088] In accordance with an embodiment, the computing device 306
may be configured to communicate control information to the second
electronic device 104 to rotate the 3-D calibration object 106, in
accordance with the determined rotation pattern in a 3-axes
rotation. The control information may be communicated via the
communication network 108, such as in a wireless communication. The
computing device 306 may be configured to communicate control
instructions to the plurality of the cameras 304A to 304D to
capture a plurality of image frames of the 3-D calibration object
106 during various rotation states of the 3-D calibration object
106.
[0089] In accordance with an embodiment, each of the plurality of
the cameras 304A to 304D may capture a plurality of image frames of
the 3-D calibration object 106 simultaneously. The computing device
306 may be configured to receive the captured plurality of image
frames from each of the plurality of the cameras 304A to 304D.
[0090] In accordance with an embodiment, the computing device 306
may be configured to detect a plurality of feature points in each
of the captured plurality of image frames of each of the plurality
of the cameras 304A to 304D. The computing device 306 may determine
a similarity of the distribution of the plurality of feature points
between each image frame of the captured plurality of image frames
and an image of the set of selected images. In this case, the
corners of the 2-D chessboard pattern 308A in each facade and/or
the colored unique identifier 308B may be the plurality of feature
points that may be detected.
[0091] In accordance with an embodiment, the computing device 306
may be configured to select the image frames from the captured
plurality of image frames that have feature point distributions
similar to one of the images in the set of selected images. In
instances when the all images in the set of pre-selected images are
matched with certain image frames from the captured plurality of
image frames, the dynamic detection and selection process may stop.
Thus, the use of the learned image set, such as the set of selected
images, may increase efficiency as it may not require capture of a
large number of images or videos for intrinsic calibration. The
intrinsic camera parameters may then be estimated for each of the
plurality of cameras 304A to 304D, based on the selected image
frames from the captured plurality of image frames. In accordance
with an embodiment, one or more known intrinsic parameter
estimation techniques may then be applied.
[0092] In accordance with an embodiment, the computing device 306
may be configured to determine a different rotation pattern
customized for calibration of extrinsic camera parameters, such as
rotation and translation parameters. The rotation may be designed
to generate as many 3-D points as possible by use of the colored
unique identifiers 308B and/or an edge that result from an
intersection between the two facades with the 2-D chessboard
pattern 308A. It may be desirable that the colored unique
identifiers 308B on each facade are as distantly distributed as
possible on the 3D-calibration object 106, such that a larger 3-D
space is covered by the colored unique identifiers 308B (such as
the 3-D points). This may result in higher accuracy when the
colored unique identifiers 308B and/or the edges are detected in
the image frames of videos that may be captured by each of the
plurality of cameras 304A to 304D. A 2-D to 3-D mapping for
calibration of extrinsic camera parameters may be performed.
[0093] In accordance with an embodiment, the computing device 306
may be configured to synchronize time-of-capture of the plurality
of image frames of the 3-D calibration object 106 with the rotation
state of the 3-D calibration object 106 at each pre-defined step
angle, such as the ".theta..sub.ex.degree.". As an orientation of
each facade of the 3-D calibration object 106 for a time instant in
the determined other rotation pattern may be known, a 2-D to 3-D
mapping for an image frame captured at the time instant in the
determined rotation pattern may be derivable. The first electronic
device 102 may be configured to determine a 2-D to 3-D mapping of
each image frame of the captured other plurality of image frames
for the calibration of extrinsic camera parameters for the
plurality of the cameras 304A to 304D. Such 2-D to 3-D mapping may
be based on the time-of-capture synchronization, the calibrated
camera intrinsic parameters, and the 3-D world coordinates of the
plurality of feature points on the 3-D calibration object 106.
During the extrinsic calibration, the plurality of cameras 304A to
304D may capture multiple perspectives of the homogeneous 2-D
texture pattern 106A, which makes the resultant accuracy more
uniform among different viewing angles. Thus, the computing device
306 may perform quick and automated calibration of intrinsic and/or
extrinsic parameters of the plurality of cameras 304A to 304D with
the same rotatable 3-D calibration object 106 with increased
accuracy.
[0094] FIGS. 4A and 4B, collectively, illustrates a first flow
chart for implementation of an exemplary method for camera
calibration by use of a rotatable 3-D calibration object, in
accordance with an embodiment of the disclosure. With reference to
FIGS. 4A and 4B, there is shown a flow chart 400. The flow chart
400 is described in conjunction with FIGS. 1A, 1B, 2, 3A and 3B.
The method, in accordance with the flow chart 400, may be
implemented in the first electronic device 102. The method starts
at step 402 and proceeds to step 404.
[0095] At step 404, a set of pre-selected images, which includes a
2-D texture pattern captured at pre-defined viewing angles, may be
received. The set of pre-selected images may correspond to the
learned image set. At step 406, a rotation pattern of the 3-D
calibration object 106 may be determined. The rotation pattern may
be determined based on the set of pre-selected images that includes
the 2-D texture pattern captured at pre-defined viewing angles.
[0096] At step 408, control information may be communicated to the
second electronic device 104, associated with the 3-D calibration
object 106. The control information may correspond to the
determined rotation pattern. The control information may be
communicated to rotate the 3-D calibration object 106, in
accordance with the determined rotation pattern. At step 410, a
plurality of image frames of the 3-D calibration object 106 may be
captured by the first electronic device 102, to calibrate intrinsic
camera parameters of the first electronic device 102.
[0097] At step 412, a plurality of feature points may be detected
in each of the captured plurality of image frames. The plurality of
feature points may correspond to the pre-defined 2-D texture
pattern 106A, and/or the unique identifier 106B, in each of the
captured plurality of image frames. An example of the plurality of
feature points may be the corners of the 2-D chessboard pattern, as
shown in FIG. 3B. At step 414, a similarity related to distribution
of the plurality of feature points between each of the captured
plurality of image frames and one of the set of pre-selected
images, may be determined.
[0098] At step 416, a set of image frames from the captured
plurality of images may be selected based on the determined
similarity. At step 418, the set of image frames may be utilized
for calibration of intrinsic camera parameters of the first
electronic device 102. At step 420, another rotation pattern of the
3-D calibration object may be determined. The other rotation
pattern may be determined for calibration of extrinsic camera
parameters for the first electronic device 102.
[0099] At step 422, other control information may be communicated
to the second electronic device 104, associated with the 3-D
calibration object 106. The other control information may
correspond to the determined other rotation pattern for the
extrinsic calibration. At step 424, another plurality of image
frames or videos of the 3-D calibration object 106 may be captured
by the first electronic device 102, to calibrate extrinsic camera
parameters of the first electronic device 102. A time-of-capture of
the other plurality of image frames of the 3-D calibration object
106 may be synchronized to a rotation state of the 3-D calibration
object 106 at a specific angle based on the determined other
rotation pattern.
[0100] At step 426, the time-of-capture of the other plurality of
image frames (or the image frames of the video) of the 3-D
calibration object 106 may be associated with a rotation state of
the 3-D calibration object 106. At step 428, a 2-D to 3-D mapping
of each image frame of the captured other plurality of image frames
may be performed. The 2-D to 3-D mapping may be based on the
time-of-capture synchronization, the estimated camera intrinsic
parameters, and pre-stored 3-D world coordinates of the plurality
of feature points that includes the unique identifiers 106B on the
3-D calibration object 106. The orientation of each facade of the
3-D calibration object 106 for a time instant in the determined
other rotation pattern may be known. Accordingly, the 2-D to 3-D
mapping for an image frame captured at a particular time instant in
the determined rotation pattern may be derivable.
[0101] At step 430, another set of image frames from the captured
other plurality of images may be selected based on the 2-D to 3-D
mapping. At step 432, the other set of image frames and the
associated 2-D to 3-D mapping information may be utilized for
calibration of extrinsic camera parameters of the first electronic
device 102. The control may pass to the end step 434.
[0102] FIGS. 5A and 5B, collectively, illustrate a second flow
chart for implementation of an exemplary method for camera
calibration by use of a rotatable 3-D calibration object, in
accordance with an embodiment of the disclosure. With reference to
FIGS. 5A and 5B, there is shown a flow chart 500. The flow chart
500 is described in conjunction with FIGS. 1A, 1B, 2, 3A, and 3B.
The method, in accordance with the flow chart 500, may be
implemented in the first electronic device 102. The first
electronic device 102 may be a computing device, such as the
computing device 306, which may be communicatively coupled to the
plurality of imaging devices 114A to 114D. The method starts at
step 502 and proceeds to step 504.
[0103] At step 504, a set of pre-selected images, which includes a
2-D texture pattern captured at pre-defined viewing angles, may be
received. The set of pre-selected images may correspond to the
learned image set. At step 506, a rotation pattern of the 3-D
calibration object 106 may be determined. The rotation pattern may
be determined based on the set of pre-selected images, which
includes the 2-D texture pattern captured at pre-defined viewing
angles.
[0104] At step 508, control information may be communicated to the
second electronic device 104, associated with the 3-D calibration
object 106. The control information may correspond to the
determined rotation pattern. The control information may be
communicated to rotate the 3-D calibration object 106, in
accordance with the determined rotation pattern. At step 510,
control instructions may be communicated to the plurality of
imaging devices 114A to 114D, to capture a plurality of image
frames of the 3-D calibration object 106 during various rotation
states of the 3-D calibration object 106, in accordance with the
determined rotation pattern. An example of the plurality of imaging
devices 114A to 114D may be the plurality of cameras 304A to 304D.
A plurality of image frames may be captured by each of the
plurality of imaging devices 114A to 114D for parallel computation
of intrinsic camera parameters of the plurality of imaging devices
114A to 114D. The plurality of imaging devices 114A to 114D may be
positioned around the 3-D calibration object 106, at a height
similar to that of the 3-D calibration object 106.
[0105] At step 512, the captured plurality of image frames of the
3-D calibration object 106 may be received from each of the
plurality of imaging devices 114A to 114D. At step 514, a plurality
of feature points may be detected in each of the captured plurality
of image frames. The plurality of feature points may correspond to
the pre-defined 2-D texture pattern 106A and/or the unique
identifier 106B in each of the captured plurality of image
frames.
[0106] At step 516, a similarity related to distribution of the
plurality of feature points between each of the captured plurality
of image frames and one of the set of pre-selected images, may be
determined. At step 518, a set of image frames from the captured
plurality of images for each of the plurality of imaging devices
114A to 114D, may be selected based on the determined
similarity.
[0107] At step 520, the selected set of image frames for each of
the plurality of imaging devices 114A to 114D, may be utilized for
calibration of intrinsic camera parameters of each of the plurality
of imaging devices 114A to 114D, simultaneously. At step 522,
another rotation pattern of the 3-D calibration object 106 may be
determined. The other rotation pattern may be determined for
calibration of extrinsic camera parameters for each of the
plurality of imaging devices 114A to 114D.
[0108] At step 524, other control information may be communicated
to the second electronic device 104, associated with the 3-D
calibration object 106. The control information may correspond to
the determined other rotation pattern for the extrinsic
calibration. At step 526, another plurality of image frames, or a
video of the 3-D calibration object 106, may be captured by each of
the plurality of imaging devices 114A to 114D. The other plurality
of image frames or the video may be captured during the various
capturing periods (described in FIG. 1B and further in FIG. 7) to
calibrate extrinsic camera parameters of the plurality of imaging
devices 114A to 114D. A time-of-capture of the other plurality of
image frames (or image frames of the captured video) of the 3-D
calibration object 106 may be synchronized to each rotation state
of the 3-D calibration object 106, at a specific angle based on the
determined other rotation pattern.
[0109] At step 528, the time-of-capture of each of the other
plurality of image frames (or the image frames of the video) of the
3-D calibration object 106 may be associated with a rotation state
of the 3-D calibration object 106. At step 530, a 2-D to 3-D
mapping of each image frame of the captured other plurality of
image frames may be performed. The 2-D to 3-D mapping may be based
on the synchronization of the time-of-capture, the estimated camera
intrinsic parameters, and pre-stored 3-D world coordinates of the
plurality of feature points that includes the unique identifiers
106B on the 3-D calibration object 106. The orientation of each
facade of the 3-D calibration object 106 for a time instant may be
known based on the determined other rotation pattern. Accordingly,
the 2-D to 3-D mapping for an image frame captured at a particular
time instant in the determined other rotation pattern may be
derivable.
[0110] At step 532, another set of image frames from the captured
other plurality of image frames for each of the plurality of
imaging devices 114A to 114D, may be selected based on the 2-D to
3-D mapping. At step 534, the other set of image frames and/or the
associated 2-D to 3-D mapping information may be utilized for
simultaneous calibration of extrinsic camera parameters of the
plurality of imaging devices 114A to 114D. The control may pass to
the end step 536.
[0111] FIG. 6 illustrates a third flow chart related to a rotation
pattern for calibration of intrinsic camera parameters for
implementation of an exemplary method for camera calibration by use
of a rotatable 3-D calibration object, in accordance with an
embodiment of the disclosure. With reference to FIG. 6, there is
shown a flow chart 600. The flow chart 600 is described in
conjunction with FIGS. 1A, 1B, 2, 3A, 3B, 4A, 4B, 5A and 5B. The
method, in accordance with the flow chart 600, may be implemented
in the second electronic device 104. The method starts at step 602
and proceeds to step 604.
[0112] At step 604, a numeric value "n.sub.in" may be set to zero
to initiate a rotation pattern for intrinsic calibration, in
accordance with control information received from the first
electronic device 102. At step 606, in instances when
"n.sub.in"="0", a first 3-axes rotation configuration for a first
image of a set of pre-selected images, may be generated.
[0113] At step 608, it may be determined whether a plurality of
rotation configurations for the first image of the pre-selected set
of images is generated. In instances when all the possible rotation
configurations for the first image of the set of pre-selected
images are generated, the control may pass to step 610. In
instances when all the possible rotation configurations for the
first image of the set of pre-selected images are not generated,
the control may pass back to step 606.
[0114] At step 610, the numeric value "n.sub.in" may be increased
by the numeric value "1" (that is "n.sub.in=n.sub.in+1"). At step
612, it may be determined whether the numeric value "n.sub.in" is
greater than a certain numeric value obtained by use of the
mathematical expression (1), that is when
"n.sub.in">"360/(.theta..sub.in.degree..times.P)". In accordance
with the mathematical expression (1), "n.sub.in" is the numeric
value, "P" is the number of facades with 2-D texture pattern 106A,
and the unique identifier 106B on the 3-D calibration object 106,
and ".theta..sub.in" is a pre-defined step angle for intrinsic
parameter calibration. In instances, when
"n.sub.in".ltoreq."360/(.theta..sub.in.degree..times.P)", the
control may pass to step 614. In instances when
"n.sub.in">"360/(.theta..sub.in.degree..times.P)", the control
passes to step 618.
[0115] At step 614, the 3-D calibration object 106 may be rotated
along a vertical axis clockwise by the pre-defined step angle
(.theta..sub.in.degree.). At step 616, when
"n.sub.in"="n.sub.in+1", another 3-axes rotation configuration for
a next image of the set of pre-selected images, may be generated.
The control may pass back to step 608. Thus, the rotation sequence
may repeat at a certain degree along the vertical axis, given by
the mathematical expression (2)
(n.sub.in.times..theta..sub.in.degree.). In accordance with an
embodiment, the smaller the pre-defined step angle
".theta..sub.in.degree.", the more likely it is to match the sample
images of the captured plurality of image frames with the learned
image set. The process may repeat until a complete rotation is
performed (that is when
n.sub.in>360/(.theta..sub.in.degree..times.P)) in accordance
with the rotation pattern determined, based on all images of the
set of pre-selected images for intrinsic camera parameters
calibration. At step 618, a stop command to halt the rotation of
the 3-D calibration object 106 may be generated. The control may
then pass to end step 620.
[0116] FIG. 7 illustrates a fourth flow chart related to another
rotation pattern for calibration of extrinsic camera parameters for
implementation of an exemplary method for camera calibration by use
of a rotatable 3-D calibration object, in accordance with an
embodiment of the disclosure. With reference to FIG. 7, there is
shown a flow chart 700. The flow chart 700 is described in
conjunction with FIGS. 1A, 1B, and 2 to 6. The method, in
accordance with the flow chart 700, may be implemented in the
second electronic device 104. The method starts at step 702 and
proceeds to step 704.
[0117] At step 704, a numeric value "n.sub.ex" may be set to zero
to initiate a rotation pattern for calibration of extrinsic camera
parameters in accordance with control information received from the
first electronic device 102. At step 706, in instances when
"n.sub.ex"="0", rotation of the 3-D calibration object 106 may be
temporally stopped at a first rotation state of the 3-D calibration
object 106, for a pre-defined duration. The pre-defined duration
may be referred to as a first capturing period. A timestamp may be
generated for the first rotation state of the 3-D calibration
object 106.
[0118] At step 708, the numeric value "n.sub.ex" may be increased
by the numeric value "1" (that is "n.sub.ex=n.sub.ex+1"). At step
710, it may be determined whether the numeric value "n.sub.ex" is
greater than a certain numeric value obtained by use of the
mathematical expression (3), that is when
"n.sub.ex>360/(.theta..sub.ex.degree..times.P)". In accordance
with the mathematical expression (3), "n.sub.ex" is the numeric
value used for calibration of extrinsic camera parameters, P is the
number of facades with 2-D texture pattern 106A and the unique
identifier 106B on the 3-D calibration object 106, and
".theta..sub.ex" is a pre-defined step angle for extrinsic camera
parameter calibration. In instances when
"n.sub.ex.ltoreq.360/(.theta.ex.degree..times.P)", the control may
pass to step 712. In instances when
"n.sub.ex>360/(.theta..sub.ex.degree..times.P)", the control
passes to step 714.
[0119] At step 712, the 3-D calibration object 106 may be rotated
along a vertical axis clockwise by the pre-defined step angle
".theta..sub.ex.degree.". At step 714, when
"n.sub.ex"="n.sub.ex+1", rotation of the 3-D calibration object 106
may be temporarily stopped at a next rotation state of the 3-D
calibration object 106. The rotation of the 3-D calibration object
106 may be temporarily stopped for the pre-defined duration that
may be a next capturing period for the first electronic device 102
(when implemented as an imaging device) or the plurality of imaging
devices 114A to 114D. A timestamp may be generated for each
rotation state of the 3-D calibration object 106. The control may
pass back to step 708. Thus, the rotation sequence may repeat at a
certain degree along the vertical axis, given by the mathematical
expression (4) (n.sub.ex.times..theta..sub.ex.degree.). The process
may repeat until a complete rotation is performed (that is when
n.sub.ex>360/(.theta..sub.ex.degree..times.P)) in accordance
with the received control information from the first electronic
device 102, which corresponds to the other rotation pattern
determined for the extrinsic camera parameters calibration. At step
716, the rotation of the 3-D calibration object 106 may be stopped.
The control may then pass to the end step 718.
[0120] In accordance with an embodiment of the disclosure, the
system for camera calibration, by use of the rotatable 3-D
calibration object 106, may comprise the first electronic device
102 (FIG. 1A). The first electronic device 102 may comprise one or
more circuits, such as the processor 202 (FIG. 2). The processor
202 may be configured to determine a rotation pattern of the 3-D
calibration object 106 (FIGS. 1A, 1B, and 3B). The rotation pattern
may be determined based on a set of pre-selected images, such as
the learned image set, which includes a 2-D texture pattern
captured at pre-defined viewing angles. The processor 202 may be
configured to communicate control information to the second
electronic device 104, associated with the 3-D calibration object
106, to rotate the 3-D calibration object 106, in accordance with
the determined rotation pattern. A plurality of image frames of the
3-D calibration object 106 may be captured to calibrate intrinsic
and/or extrinsic camera parameters of the first electronic device
102.
[0121] Various embodiments of the disclosure may provide a
non-transitory computer readable medium and/or storage medium,
and/or a non-transitory machine readable medium and/or storage
medium with a machine code stored thereon, and/or a set of
instructions executable by a machine and/or a computer for camera
calibration by use of the rotatable 3-D calibration object 106. The
set of instructions in the first electronic device 102 may cause
the machine and/or computer to perform the steps that include
determination of a rotation pattern of the 3-D calibration object
106 (FIGS. 1A, 1B, and 3B). The rotation pattern may be determined
based on a set of pre-selected images that may include a 2-D
texture pattern captured at pre-defined viewing angles. Control
information may be communicated to the second electronic device 104
(FIG. 1A), associated with the 3-D calibration object 106. The
control information may be communicated to rotate the 3-D
calibration object 106, in accordance with the determined rotation
pattern. A plurality of image frames of the 3-D calibration object
106 may be captured to calibrate intrinsic and/or extrinsic camera
parameters of the first electronic device 102.
[0122] The present disclosure may be realized in hardware, or a
combination of hardware and software. The present disclosure may be
realized in a centralized fashion, in at least one computer system,
or in a distributed fashion, where different elements may be spread
across several interconnected computer systems. A computer system
or other apparatus adapted to carry out the methods described
herein may be suited. A combination of hardware and software may be
a general-purpose computer system with a computer program that,
when loaded and executed, may control the computer system such that
it carries out the methods described herein. The present disclosure
may be realized in hardware that comprises a portion of an
integrated circuit that also performs other functions.
[0123] The present disclosure may also be embedded in a computer
program product, which comprises all the features that enable the
implementation of the methods described herein, and which when
loaded in a computer system, is able to carry out these methods.
Computer program, in the present context, means any expression, in
any language, code or notation, of a set of instructions intended
to cause a system that has an information processing capability to
perform a particular function either directly, or after either or
both of the following: a) conversion to another language, code or
notation; b) reproduction in a different material form.
[0124] While the present disclosure has been described with
reference to certain embodiments, it will be understood by those
skilled in the art that various changes may be made and equivalents
may be substituted without departure from the scope of the present
disclosure. In addition, many modifications may be made to adapt a
particular situation or material to the teachings of the present
disclosure without departure from its scope. Therefore, it is
intended that the present disclosure not be limited to the
particular embodiment disclosed, but that the present disclosure
will include all embodiments that falls within the scope of the
appended claims.
* * * * *